On March 8, the inaugural a2 National Symposium will feature keynote talks from experts in AI, aging, and medical technologies; a panel discussion on AI and ethics; and opportunities to learn about the first cohort of a2 Pilot Awards-funded projects and their technology solutions to improve care, health, and quality of life for older adults, including individuals with AD/ADRD, and their caregivers.
In addition to networking sessions and project posters from more than 25 Cohort 1 awardees, the symposium will feature a Pitch Competition in which seven Cohort 1 awardees will pitch their novel technology solutions live onstage. See the full list of Pitch Competition finalists below, learn more about their projects, and be sure to register for the a2 National Symposium to attend the Pitch Competition (in person or virtually) and hear the live pitches.
Bestie Bot: A home-based, AI-enabled camera system that combines stereo vision with thermal sensors to detect falls, send alerts, perform basic health diagnostics, and expand telehealth tools for flexibility measurements
PI: Richard Everts
Sequoia: A wearable technological headband capable of measuring brain activity via EEG and using AI algorithms to time the therapeutic delivery of acoustic stimulation to enhance slow-wave sleep activity
PIs: Joshua Blair, MS; Youseph Yazdi, PhD
Sovrinti: AI techniques using data from a background sensor system that combines device utilization and real-time location information to detect change in Activities of Daily Living behavior for seniors in home and assisted living environments in order to preemptively identify adverse effects in seniors with cognitive challenges
PI: John Fitch
WAVi: Refinement of standard clinical EEG methods with machine learning for early detection of age-related cognitive decline
PIs: Francesca Arese Lucini, PhD; Anqi Liu, PhD
Virtual Apprentice: A simulated 360 immersive environment to mitigate the effects of social isolation and minimal cognitive stimulation on older adults
PI: Ellie Giles, EdD
Visilant: A simple and inexpensive anterior segment imaging and telemedicine system to allow for remote eye screening by non-ophthalmologists for cataract screening, referral, and post-operative management for older adults
PIs: Kunal Parikh, PhD; Nakul Shekhawat, MD, MPH
WellSaid.ai: Machine learning models to accurately predict the cognitive status of older adults in their home using cognitive performance tests administered by Alexa and Google Assistant devices
PI: Randy Williams, MD
Following the symposium, watch our blog for the announcement of the Pitch Competition winner and highlights from symposium sessions and poster presentations.